Sentiment Analysis of Practo App Reviews using KNN and Word2Vec

Abstract

The development of technology and communication is used by the community to facilitate daily activities, one of which is in the field of health services. Health services are good enough, but there are still some obstacles that are commonly found, including not allowing to leave the house or a short schedule of doctor consultations. With the presence of health service applications, one of which is Practo, it makes it easier for people to consult online. This convenience makes a lot of reviews regarding the Practo healthcare application. The diversity of opinions on the internet, makes Practo app reviews varied. Therefore, sentiment analysis of Practo app reviews is necessary. In this study, the algorithm used was KNN. The KNN algorithm was chosen because it is very effective if the amount of data is large and easy to implement. The feature extraction used in this study is Word2Vec. Word2Vec was chosen as a feature extraction because it was considered good enough to use because it represented each word with a vector. This research produced the best model built when using stemming with Word2Vec dimensions of 300 and K = 3 values on the KNN parammeter, capable of producing an f1-score of 77.30%.